Course Schedule

Day 1 - Wednesday 09 December, 2020
Opening Session

Opening Remarks  & Introduction

Session One (11:00 To 12:00)

The Introduction to the problem of Medical Insurance Fraud

  • Medical Insurance Fraud and its implications for society and economies.
  • Major Types of Fraud, waste, and abuse in healthcare insurance industry
Break (20 minutes)
Session Two (12:20 To 13:20)

The Introduction to Data Analytics / Data Science
The Evidence of Healthcare Fraud and How to Collect it / Discuss what data to analyze
What is Data Analytics?

  • Descriptive, Diagnostic, Predictive and Prescriptive
  • Importance of Descriptive & Diagnostic Analytics
  • When we need Predictive & Prescriptive Analytics

Fundamentals of Descriptive Analytics – Exploratory Data Analysis (EDA) / BI Reports / Visualization Dashboards

  • How to do efficient EDA?
  • How to develop effective and outcome driven dashboards?
  • What KPIs to report?
Break (20 minutes)
Session Three (13:40 To 14:40)

AI / Machine Learning 101 and Its Applications In Healthcare
Fundamentals of Predictive & Prescriptive Analytics – Machine Learning

  • Major types of Machine Learning (e.g., classification, regression, association rules, clustering, text analytics, anomaly / outlier detection, etc) and relevant examples
  • Common use cases where Machine Learning is used but you may not know it
  • Common health care use cases where data analytics is used today
Day 2 - Thursday 10 December, 2020
Session One (11:00 To 12:00)

Data Analytics Applications in Health care Fraud Waste and Abuse – EDA, Reporting & Dashboards
Review of previous day learning sessions and data analytics discussed

  • What kind of data is available for the data analytics
  • What kind of EDA is useful in health care fraud?
  • How to convert your FWA expertise into business rules that could be run automatically every day / hour / week? – Case studies and Roundtable discussion
  • Examples of visualization dashboards / tools to help fraud investigation
  • Possible demo of some of these visualization tools / dashboards
Break (20 minutes)
Session Two (12:20 To 13:20)

Predictive / Prescriptive Analytics in Action to combat Health Care Fraud
How advanced data analytics could be used to fight health care FWA?

  • Business rules – quick review from yesterday
  • Classification models – detecting variations of know health care fraud
  • Anomaly / Outlier Detection – detecting novel types of health care fraud

Doing your homework – assets, marital and financial status, bankruptcies/divorces/ substance abuse data

Break (20 minutes)
Session Three (13:40 To 14:40)

Predictive / Prescriptive Analytics in Health Care Fraud Detection - Case Studies and Round Table Discussions

  • Data Analytics for Post-pay vs. Pre-Pay
  • Reviewing actual use cases of successful investigations from advanced data analytics
  • Round table discussion on possible fraud use cases and how data analytics could help
  • Round table discussion and review of the course

Quiz and discussion of responses

Course Program
Time Topic
Day 1
10:45 to 11:00Registration & Introduction
Day 1-2
11:00 to 12:00Session One
12:00 to 12:20Break (20 minutes)
12:20 to 13:20Session Two
13:20 to 13:40Break (20 minutes)
13:40 to 14:40Session Three